Project PPT on time table scheduler using genetic algorithm with code.

1. TIME TABLE
SCHEDULER

2. TEAM MEMBERS:
1) SHASWAT (1405248) : SCRUM MASTER
2)CHANDRABALI GUHA (1405): TECH LEAD
3)TALMEEZ FAIZY (1405267): CODER
4)DEBOTOSH SARKAR (1405) : CODER
5)LAVANYA RAJ (1405226) : TESTER

3. TEAM ROLE PLAY:

4. PROBLEM
DESCRIPTION
Lets see why you need our product !!!!!

5. SCHEDULING OF A TIME TABLE HAS BEEN A
CHALLENGING TASK FOR ANY ORGANISATION ,
SPECIALLY FOR UNIVERSITIES HAVING A LARGE
NUMBER OF STUDENTS AND FACULTIES ,
WORKING IN MULTIPLE SHIFTS , TAKING CARE OF
THE AVAILABLILITY OF THE CLASSROOMS . WITH
SO MANY FACTORS IN STAKE IT TAKES A LOT OF
BRAINSTORMING FOR THE PERSON ASSIGNED TO
DESIGN THIS SCHEDULE AND IT ALSO SOMETIMES
LEADS TO AMBIGUOUS RESULTS WITH A CLEAR
STATE OF DISSATISFACTION AMONGST THE
FACULTIES AND STUDENTS .

7. The aim of this product is the generation of course
schedules while demonstrating the possibility of
building these schedules automatically through the
use of computers in such a way that they are optimal
and complete with little or no redundancy through the
development of a viable lecture timetabling software.

8. REQUIREMENT GATHERING

9. IN ORDER TO COLLECT THE EXACT
REQUIREMENTS WE FIRST OF ALL
DISTINGUISHED OUR STAKE HOLDERS AS
FOLLOWS :
1) STUDENTS
2) FACULTIES
We went to a few members of both the stake holders to
interview them and collect the necessary requirements . We
analysed the answers given by our stakeholders to understand
the requirements

10. QUESTIONARE FOR STUDENTS:
1) How many hours of lecture is preferred by you in a day ?
2) What should be the time span for breaks between classes
?
3) How many lectures simultaneously is preferred by you ?
4) A week should be 6 working days or 5 working days ?
5) What should be the number of half days provided in a
week ?
6) What should be the working hours of the college ?

11. QUESTIONARE FOR FACULTIES:
1) How many hours of lecture is preferred by you in a day ?
2) What should be the time span for breaks between classes ?
3) How many lectures simultaneously is preferred by you ?
4) A week should be 6 working days or 5 working days ?
5) What should be the number of half days provided in a week ?
6) What should be the working hours of the college ?
7) Are you satisfied with the existing system ?

12. RESOURCE ANALYSIS:
1) NO OF CLASSROOMS AVAILABLE IN THE BUILDING
2) NO OF FACULTIES IN THE DEPARTMENT
3) NO OF SECTIONS IN EVERY YEAR
4) FACULTY DETAILS
5) STUDENT DETAILS
6) COURSES OFFERED

13. LIMITATIONS OF THE EXISTING SYSTEM
• Repeated time allocations may be made for a particular course
thereby leading to data redundancy.
• A lot of administrative error may occur as a result of confusing time
requirements.
• Timetable generation by center staff may have a slow turnaround.
• Final generated timetable may not be near optimal as a result of
clashing course requirements and allocations.
• It generates a lot of paperwork and is very tasking.
• It is not flexible as changes may not be easily made

14. SYSTEM DESIGN
System design is the specification or
construction of a technical, computer-based
solution for the business requirements
identified in a system analysis.
Modeling a system is the process of
abstracting and organizing significant
features of how the system would look like

15. Use Case Diagram to
show the interaction
between the user and
the system

16. Class Diagram to show
the relationships
between the different
classes associated with
the system

17. Sequence Diagram to
show how the different
objects interact during
the execution of the
system

18. Activity Diagram to model the actions and the
output of those actions when an operation is
carried out in the system

19. State Diagram to depict the different states of the
system during its execution

20. SYSTEM IMPLEMENTATION
The system implementation defines the construction,
installation, testing and delivery of the proposed system

21. BIG
CONCEPTThe brain behind this product

22. TIME TABLING AS A NP-COMPLETE PROBLEM
NON DETERMINISTIC POLYNOMIAL TIME COMPLETE PROBLEM
 ANY SOLUTION TO THE PROBLEM CAN BE VERIFIED
VERY QUICKLY
 IF THE PROBLEM CAN BE SOLVED QUICKLY THEN DO
EVERY PROBLEM IN NP
Genetic algorithm have been the most prominently used in
genetically near optimal solution to time table problems , hence
it’s usage in implementation of the project

23. GENETIC ALGORITHM
• Search algorithm based on the mechanism of natural
selection and natural genetic.
• Based on the “survival of the fittest” concept.
• Stimulates the process of evaluation

24. WHO DEVELOPED IT ?
 Developed by Prof.John Holland, his colleagues and students
at the University of Michigan around 1975.
 Prof David Goldberg-illustrious student of Holland and author
of “Genetic Algorithms in search , optimization and machine
learning, Addison Wesley-1989”.
 Central theme of research on genetic algorithms

25. WHY GENETIC ALGORITHM ?
BECAUSE IT CONVERGES TO THE GLOBAL POINTS
ALWAYS

26. METHODOLOGY OF GENETIC ALGORITHM
METHOD 1
1.In a genetic algorithm, a population of candidate solutions
to an optimization problem is evolved toward better solutions
2.Each candidate solution has a set of properties which can
be mutated and altered
3.Traditionally, solutions are represented in binary as strings
of 0’s and 1’s but other encodings are also possible .
e.g: 1011010010

27. METHODOLOGY OF GENETIC ALGORITHM
METHOD 2
1.The evaluation starts from a population of randomly generated individuals, and is an
alternative process, with the population in each iteration called a generation.
2.In each generation , the fitness of every individual in the population is evaluated : the
fitness is usually the value of the objective function in the optimization problem being
solved
3.The more fit individual are stochastically selected from the current population, and
each individual’s genome is modified.
4.The new generation of candidate solutions is then used in the next iteration of the
algorithm.
5.Commonly, the algorithm terminates when either a maximum number of generations
has been produced, or a satisfactory fitness level has been reached for the population

28. OUTLINE OF GENETIC ALGORITHM
1. START
2. FITNESS
3. NEW POPULATION
3.1 SELECTION
3.2 CROSSOVER
3.3 MUTATION
3.4 ACCEPTING
4. REPLACE
5. TEST
6. LOOP

29. ELLITISM
TO PREVENT THE CHROMOSOMES TO LOSE THEIR FITNESS ,
THEY ARE ELIMINATED FROM CROSSOVER AND PASSED ON
DIRECTLY TO NEXT GENERATION

30. GENETIC OPERATORS
• SELECTION
• MUTATION
• CROSSOVER

31. Selection
for taking
input

32. FITNESS
CLASS OF
GENTETIC
ALGORITHM

33. MUTATION
FUNCTION

34. System Requirements
»Processor should be Pentium 5 and above
»128 Megabytes of RAM (or more)
»1 Gigabyte of Free Disk SpaceAnd some text
»Windows XP or above
»Microsoft excel 2003 or above

35. FUTURE SCOPE

36. EROOR
HANDLING
FEATURES
TEST-CASESG.U.I
SCOPE FOR FURTHER WORKS

37. COMMERCIAL ASPECT
The algorithm can be implemented in other organisations like :
1. Hospital bed management system
2. Plants and other industries to schedule the shift of the workers
3. Schools

38. CREDITS
Special thanks to Dr Prachyet Bhuyan Sir for guiding us
throughout the implementation of project

39. THANKS!
😉